Performance of an automatic translation device has been gradually improved, however, translation results of the automatic translation device still contains lots of errors or faults. The automatic translation device performing a rule-based or pattern-based translation particularly shows unsatisfactory translation results with unnatural or ungrammatical sentences.
Some of these errors can be solved by improving separate modules included in a translation engine, however, because the separate modules do not consider a sentence as a whole, the errors are still likely to occur. Therefore, a function of automatically correcting errors occurring in a final translation is required to upgrade a performance of an automatic translation device.
Further, most of automatic translation devices are mainly used for desktop computers or servers. These types of automatic translation devices generally perform an automatic translation on already digitalized text files, web documents, PDF files and the like.
However, there exist various types of offline texts required to be translated, e.g., menus for restaurants, sign boards on the street, hard copy documents and the like.
Conventionally, there has been an automatic translation device for a mobile device, which includes a character recognition module to provide an automatic translation function.
However, the conventional automatic translation device has a shortcoming of a poor quality of translation due to a limitation of character recognition technologies.